JP2017049036A - Image measuring device and control program thereof - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image measuring device capable of performing suitable measurement and its control program.SOLUTION: An image measuring device according to one embodiment of the present invention comprises: an imaging device for photographing a work and obtaining an image of the work; and an arithmetic device for performing measurement of the work on the basis of the image and outputting a measurement result. Furthermore, the arithmetic device generates another image with fewer number of pixels than the image on the basis of the image, sets a plurality of regions on the basis of the other image, and calculates the measurement result on the basis of the plurality of regions.SELECTED DRAWING: Figure 3

Description

  The present invention relates to an image measuring apparatus that measures a workpiece by imaging the workpiece and a control program therefor.

  2. Description of the Related Art Measuring apparatuses that perform dimension measurement and shape measurement on a workpiece are known. As such a measuring apparatus, for example, an image including an imaging apparatus that captures an image of a workpiece and acquires an image of the workpiece, and an arithmetic unit that performs dimension measurement or shape measurement of the workpiece based on the image. A measuring apparatus is known (Patent Document 1). In such measurement, for example, the center position, shape, contour, width, etc. of the measurement target are calculated.

JP 2001-241941 A

  For example, when a workpiece is measured using an image measuring device, there are cases where it is not possible to suitably perform dimension measurement or shape measurement due to the influence of noise included in the image.

  The present invention has been made in view of the above points, and provides an image measurement apparatus and a control program therefor that are capable of reducing noise in an image and suitably performing dimension measurement, shape measurement, and the like. It is aimed.

  In order to solve this problem, an image measurement apparatus according to an embodiment of the present invention includes an imaging apparatus that captures an image of a workpiece and acquires an image of the workpiece, and the dimension measurement and shape of the workpiece based on the image. And an arithmetic unit that performs measurement or the like and outputs measurement results such as the center position of the measurement target, shape, contour line, and width. The arithmetic unit generates another image having a smaller number of pixels than the image based on the image, sets a plurality of regions based on the other image, and performs the measurement based on the plurality of regions. Calculate the result.

  For example, the arithmetic unit can acquire an edge point group by performing an edge detection process along the outline of the region. Further, the arithmetic device can exclude some of the plurality of edge points included in the edge point group. In addition, the arithmetic device can set a plurality of different numbers for the plurality of regions.

  The control program of the image measuring apparatus according to one embodiment of the present invention is an imaging apparatus that captures an image of a workpiece and obtains an image of the workpiece, performs dimension measurement or shape measurement of the workpiece based on the image, The measurement result is calculated by controlling an image measurement device including a calculation device that outputs a measurement result such as a center position of the measurement target, a shape, a contour line, and a width. In this program, the arithmetic unit generates another image having a smaller number of pixels than the image based on the image, sets a plurality of areas based on the other image, and sets the plurality of areas in the plurality of areas. Based on this, the measurement result is calculated.

  According to the present invention, it is possible to provide an image measuring apparatus and a control program thereof capable of suitably performing dimension measurement and shape measurement.

1 is an overall view of an image measurement apparatus according to a first embodiment of the present invention. The display screen of the image of the work acquired with the image measuring device is shown. It is a block diagram which shows the structure of the image measuring device. It is a flowchart which shows operation | movement of the image measuring device. The image pyramid produced | generated in the same operation | movement is shown. 3 is a graph showing a relationship between a pixel position and a density level along the AA line in FIG. 2. The display screen which displays the area | region set to the image of the workpiece | work in the same operation is shown. The display screen which displays the edge detection tool used in the same operation is shown. It is an enlarged view of the part shown by B of FIG. 10 shows a plurality of edge points selected from the edge points of FIG. The display screen which displays the measurement result acquired in the same operation is shown. The some edge point acquired in the conventional image measuring apparatus is shown. 13 shows a plurality of edge points selected from the edge points in FIG. The several edge point acquired from the image after filtering in the conventional image measuring apparatus is shown. The some edge point selected from the edge point of FIG. 14 is shown. The area | region set to the image of the workpiece | work by the image measuring device which concerns on the 2nd Embodiment of this invention is shown. The area extracted from the area of FIG. 16 is shown.

[First Embodiment]
Next, a first embodiment of the present invention will be described in detail with reference to the drawings.

  First, a schematic configuration of the image measuring apparatus according to the present embodiment will be described with reference to FIG.

  As shown in FIG. 1, the image measuring apparatus according to the present embodiment includes X, Y, and Z axes that are orthogonal to each other, and a camera 141 is mounted as an imaging apparatus that images the workpiece 3 at the tip of the Z axis. An image measuring machine 1 and a computer (hereinafter referred to as “PC”) 2 connected to the image measuring machine 1 are provided.

  The image measuring machine 1 is configured as follows. That is, the sample stage 12 is placed on the sample moving means 11 so as to coincide with the horizontal plane with the upper surface as a base surface, and the arm supports 13 a and 13 b erected from both ends of the sample moving means 11. The X-axis guide 13c is supported at the upper end. The sample stage 12 is driven in the Y-axis direction by the sample moving means 11. The imaging unit 14 is supported by the X-axis guide 13c so as to be driven in the X-axis direction. A camera 141 is attached to the lower end of the imaging unit 14 so as to be driven in the Z-axis direction.

  In the present embodiment, the form of imaging the workpiece 3 arranged on the sample stage 12 is taken. However, other formats may naturally be used. For example, the workpiece placed on the floor is imaged from the lateral direction. The format is acceptable. As the camera 141, various cameras such as a CCD and a CMOS can be used. As the camera 141, an image probe that can be attached to and detached from the image measuring device 1 can be adopted.

  The PC 2 includes an arithmetic device 22, a display device 21 connected to the arithmetic device 22, and an input device 23. The arithmetic device 22 includes a storage device such as a CPU and a hard disk. The display device 21 is, for example, a display or a projector. The input device 23 is an operation input device that inputs a measurement person's operation, and is, for example, a mouse, a keyboard, a touch panel, or the like.

  Next, an image displayed on the screen of the display device 21 will be described with reference to FIG.

  As shown in FIG. 2, an image of the work 3 acquired by the camera 141 (hereinafter referred to as image (3) in the figure) is displayed on the screen of the display device 21. In the example shown in FIG. 2, the work 3 includes a measurement object 31.

  Next, with reference to FIG. 3, the configuration of the arithmetic unit 22 according to the present embodiment will be described in more detail.

  As shown in FIG. 3, in the image measurement device according to the present embodiment, camera 141 captures workpiece 3 and acquires an image of workpiece 3. In addition, this image is transferred to the display device 21 via the arithmetic device 22. In addition, the arithmetic device 22 accepts a measurement person's operation via the input device 23, and measures the workpiece 3 (such as dimension measurement or shape measurement) based on this. For example, a part to be measured is extracted from the image, and a value relating to the position such as the center of gravity and a value relating to the shape such as the contour line and width are calculated for the measurement object.

  As illustrated in FIG. 3, the arithmetic device 22 realizes the following functions by a program stored in a CPU, a memory, a hard disk (storage device 24), and the like. That is, the area dividing unit 221 performs area dividing processing on the image of the work 3. For example, as shown in FIG. 7, region division processing is performed on the image to divide the image into a plurality of regions, and the plurality of regions are output. For example, as illustrated in FIGS. 8 and 9, the edge detection unit 222 performs edge detection processing on the outline of the output region, and acquires an edge point group including a plurality of edge points. For example, as illustrated in FIG. 10, the abnormal point removing unit 223 determines and removes some of the plurality of edge points as abnormal points, and acquires the remaining as selected edge point groups. The measurement result acquisition unit 224 acquires the measurement result based on the selected edge point group.

  Next, the operation of the image measurement apparatus according to the present embodiment will be described with reference to FIGS.

  First, step S101 will be described with reference to FIGS.

  As shown in FIGS. 4 to 7, in step S <b> 101, region division processing is performed on the image of the work 3. The area division processing can be performed in various modes. In the following, a method using an image pyramid will be exemplified. The image pyramid is a set of the same images having different resolutions (number of pixels) as shown in FIG. 5, for example.

  As shown in FIG. 5, in step S <b> 101, for example, an image pyramid is generated based on the image of the work 3. For example, as shown in FIG. 5, when the image of the work 3 is an image of n pixels, for example, the gradation of pixels adjacent in the vertical and horizontal directions is averaged to generate an image having a smaller number of pixels than the first image To do. Subsequently, similar processing is performed on the generated image to generate an image having a smaller number of pixels. Similarly, images are sequentially generated so that a newly generated image has a smaller number of pixels than the original image, and an image pyramid is generated. Subsequently, an image of k (<n) pixels is selected from a plurality of images included in the image pyramid.

  Also, as shown in FIGS. 6 and 7, in step S101, for example, a plurality of regions are set in the selected k-pixel image. The area can be set in various modes. In the example shown in FIG. 6, the portion where the density level (gradation) is higher than the threshold value Th and the density level (gradation) are set. The region is set so that the portion lower than the threshold value Th is divided into different regions. In addition, when setting an area | region according to the density level (gradation) of each pixel, it is also possible to set multiple threshold value Th. It is also possible to determine a rough position or the like of each area based on the k pixel image, and to determine the boundary of each area in detail based on the n pixel image acquired by the camera 141.

  Next, step S102 will be described with reference to FIG. 4, FIG. 8, and FIG.

  As shown in FIGS. 4, 8, and 9, in step S <b> 102, edge detection processing is performed on at least a part of the plurality of regions acquired in step S <b> 101 to acquire a plurality of edge points. The edge detection process can be performed in various modes. In the example shown in FIG. 8, a tool t for edge detection is used. The edge detection tool t illustrated in FIG. 8 includes four boxes b, and each box b has a rectangular shape extending along a contour line of a region corresponding to the measurement target 31. Each box b is provided with a plurality of line segments l extending in the short direction along the longitudinal direction. In edge detection, as shown in FIG. 8, each box b is superimposed on the contour of the measurement object 31, and a pixel having the largest change (gradient) in density level along the line segment l in the box b is acquired as an edge point. Is done.

  Next, step S103 will be described with reference to FIGS.

  As shown in FIGS. 4 and 10, in step S103, an abnormal point detection process is performed to remove abnormal points from the plurality of edge points shown in FIG. 9 and acquire selected edge points. The abnormal point detection processing can be performed in various modes. For example, an approximate straight line (approximate curve) is set at a plurality of edge points acquired in step S102, and each edge is determined from the approximate straight line (approximate curve). It is possible to calculate the distance to the point and determine the abnormal point based on the average value and the variance value of the calculated distance.

  Next, step S104 will be described with reference to FIGS.

  As shown in FIGS. 4 and 11, in step S <b> 104, for example, the measurement result is acquired based on the plurality of selected edge points acquired in step S <b> 103. In step S104, various values such as the center of gravity, contour line, and width of the measurement target (for example, measurement target 31) can be calculated.

  Here, in the conventional image measuring apparatus, when the edge detection process is directly performed on the image acquired by the camera 141, as shown in FIG. 12, due to the influence of noise included in the image, the contour of the measurement target 31 is detected. There are cases where many distant points are calculated as edge points. When an abnormal point detection process is performed on such an image, many edge points are removed as shown in FIG. 13, which may affect the measurement accuracy.

  In view of these points, in the conventional image measurement device, image processing such as filtering is performed in advance on an image acquired by the camera 141 to reduce noise in the image, and then edge detection processing is performed. was there. For such filtering, for example, an image filter such as a median filter, an average filter, a Gaussian filter, or a morphology filter may be used. However, even when image processing such as filtering is performed in this way, as shown in FIG. 14, many points away from the contour of the measurement target 31 may be calculated as edge points. Therefore, even when the abnormal point detection process is performed on such an image, as shown in FIG. 15, many edge points are removed, which may affect the measurement accuracy.

  In such a case, in the first embodiment, the image obtained by the camera 141 is subjected to region division processing to divide the image into a plurality of regions (see FIG. 7). Edge detection processing is performed on at least a part (see FIG. 8), abnormal point detection processing is performed on a plurality of edge points acquired by the edge detection processing (see FIG. 10), and measurement is performed based on the result. The result is acquired (see FIG. 11). Therefore, as shown in FIG. 7, it is possible to suitably reduce noise in the vicinity of the outline of the measurement target 31, and to obtain a large number of edge points on the outline of the measurement target 31 as shown in FIG. Further, it is possible to reduce the number of edge points to be removed in the abnormal point detection process as compared with the case described above.

  In the example described with reference to FIGS. 4 to 11, the region dividing process is performed using the image pyramid. That is, the approximate position of each region is determined based on an image having a smaller number of pixels than the image acquired by the camera 141. Here, in an image having a small number of pixels, noise included in the original image is greatly reduced. Therefore, by determining the approximate position of each region based on this image, it is possible to determine the contour of each region while reducing the influence of noise near the contour of the measurement object 31.

  Further, as described above, in the region division processing, the approximate position of each region is determined based on the k pixel image, and the boundary of each region is determined based on the n pixel image acquired by the camera 141. It is also possible to decide in detail. In such a case, the outline of the region can be determined based on an image of n pixels, so that detailed measurement can be performed while reducing noise. In addition, it is also possible to perform a high-speed rough calculation process by calculating a measurement result based on an image of k pixels.

[Second Embodiment]
Next, an image measuring apparatus according to a second embodiment of the present invention will be described with reference to FIGS. In the following description, the same parts as those in the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The image measurement apparatus according to the present embodiment is basically configured in the same manner as in the first embodiment, but in this embodiment, as shown in FIG. 16, image division processing is performed. Later, different numbers are assigned to each area. After that, as shown in FIG. 17, the area “3” corresponding to the measurement object 31 is extracted, and the measurement result is acquired based on the extracted area.

  In the present embodiment, as shown in FIG. 16, the areas “6” and “7” corresponding to the noise portion are assigned different numbers from the area “3” corresponding to the measurement target 31. Therefore, when the region “3” corresponding to the measurement target 31 is extracted, noise near the contour of the measurement target 31 can be suitably reduced.

  In this embodiment, the extracted region “3” is subjected to processing such as edge detection and abnormal point detection processing as in the first embodiment, and the measurement result is obtained based on the result. You can also get it. Moreover, a measurement result can also be acquired by performing other processes.

  In addition, as shown in FIG. 16, the areas “6” and “7” corresponding to the noise portion may have a smaller area than the other areas. Therefore, for example, after setting a threshold value for the area of a region and assigning a different number to each region, there are regions “6” and “7” where the area is equal to or less than the threshold value. In such a case, these areas “6” and “7” can be determined as areas corresponding to noise components, and can be excluded when calculating the measurement result.

[Other embodiments]
In the first embodiment, edge detection processing, abnormal point detection processing, and the like are performed. However, these processing can be omitted or replaced with other processing. It is also possible to combine image processing such as filtering.

  In addition to the case where the camera 141 is configured so that the camera 141 can be driven in the Z-axis direction and can measure coordinates in the Z-axis direction, a two-dimensional image measuring machine and an image measuring function are used. It is also applicable when using a microscope having

  DESCRIPTION OF SYMBOLS 1 ... Image measuring machine, 2 ... Computer (PC), 3 ... Workpiece, 11 ... Sample moving means, 12 ... Sample stand, 13a, b ... Arm support, 13c ... X-axis guide, 14 ... Imaging unit, Display device 21 , Arithmetic unit 22, input devices 23, 141... Camera.

Claims (5)

An imaging device that captures an image of the workpiece and obtains an image of the workpiece;
An arithmetic unit that measures the workpiece based on the image and outputs a measurement result;
The arithmetic unit is:
Based on the image, generate another image having fewer pixels than the image,
Set a plurality of areas based on the other images,
The image measurement apparatus that calculates the measurement result based on the plurality of regions. The image measurement device according to claim 1, wherein the arithmetic device performs edge detection processing along a contour line of the region to acquire an edge point group. The image measuring device according to claim 2, wherein the arithmetic device excludes a part of a plurality of edge points included in the edge point group. The image processing device according to claim 1, wherein the arithmetic device sets a plurality of different numbers for the plurality of regions. An imaging device that captures an image of the workpiece and obtains an image of the workpiece;
A control program for an image measurement device that performs measurement of the workpiece based on the image and controls the image measurement device including an arithmetic device that outputs a measurement result, and calculates the measurement result;
The arithmetic unit is:
Based on the image, generate another image having fewer pixels than the image,
Set a plurality of areas based on the other images,
A control program for an image measuring apparatus, wherein the measurement result is calculated based on the plurality of regions.